Image Augmentations for Semantic Segmentation and Object Detection

In his talk, Vladimir will talk about image augmentations. What are they? How to use them to improve Deep Learning models? He will talk about the latest research results and types of augmentations used in the winning solutions of various Deep Learning competitions.

Bio: Sr. Computer Vision Engineer at Lyft, Ph.D. Physics, Evangelist at ods.ai, Kaggle Grandmaster Vladimir got his Ph.D. in Theoretical Condensed Matter Physics at UC Davis. After graduation he was developing Energy Disaggregation algorithms that were a combination of the signal processing and machine learning techniques, working as a data scientist at Bidgely. After this, he moved to San Francisco to work in TrueAccord where he was mainly focussed on building recommender systems. Currently, Vladimir is applying Deep Learning techniques to the computer vision problems at the Lyft's Level5 Engineering Centre that is focussed on the development of the self-driving cars.